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Mining large-scale GPS streams for connectivity refinement of road maps

computer Journal 2014年第9期58卷 2109-2119页

作者： Zhu, Yanmin Wang, Yin Forman, George Wei, Hong Shanghai Key Lab of Scalable Computing and Systems Shanghai China Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China Facebook Menlo Park United States HP Labs Palo Alto United States

As people increasingly rely on road maps in the digital age, manually maintained maps cannot keep up with the demand for accuracy and freshness, evidenced by the recent iOS map incident and the bidding war for Waze. There are many research works on automatic map inference using GPS data, and some have suggested that Google and Waze automate their map update processes to some degree with user data. However, existing published work focuses on refining road geometry. In reality, connectivity issues at intersections, including missing connections and unmarked turn restrictions, are much more prevalent and also more difficult to infer. In this paper, we report our study on the connectivity issues in the OSM shanghai map using 21 months of GPS data from over $10\,000$ taxis. We first adapt a robust map matching algorithm. Then, we propose simple algorithms for detecting missing intersections, turn restrictions and road closures. Empirical results show that our algorithms of connectivity refinement for road maps are effective. © 2015 The British computer Society. All rights reserved.

关键词： Global positioning system

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Correlative Filters for Convolutional Neural Networks

Correlative Filters for Convolutional Neural Networks

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IEEE International Conference on systems, Man and Cybernetics

作者： Peiqiu Chen Hanli Wang Jun Wu Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai China Department of Computer Science and Technology Tongji University Shanghai China

ISBN: (纸本)9781479986989

This paper introduces a regularization method called Correlative Filter (CF) for Convolutional Neural Network (CNN), which takes advantage of the relevance between the convolutional kernels belonging to the same convolutional layer. During the process of training with the proposed CF method, several pairs of filters are designed in a manner of randomness to contain opposite weights in low-level layers. Regarding higher level layers where synthetical features are processed, the relation between correlative filters is explored as translation of various directions. The proposed CF method attempts to optimize the inner structure of convolutional layers and it can work jointly with other regularization techniques, such as stochastic pooling, Dropout, etc. The experimental results on the competitive image classification benchmark dataset CIFAR-10 demonstrates the performance of the proposed CF method, additionally, it is also verified that the proposed CF method is wonderful to be employed to enhance several state-of-the-art regularization models.

关键词： Feature extraction Neurons Training Stochastic processes Convolution Kernel Biological neural networks

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Coupled group lasso for web-scale CTR prediction in display advertising 31

Coupled group lasso for web-scale CTR prediction in display ...

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31st International Conference on Machine Learning, ICML 2014

作者： Yan, Ling Li, Wu-Jun Xue, Gui-Rong Han, Dingyi Department of Computer Science and Engineering Shanghai Key Laboratory of Scalable Computing and Systems Shanghai Jiao Tong University China Department of Computer Science and Technology National Key Laboratory for Novel Software Technology Nanjing University China Alibaba Group China

ISBN: (纸本)9781634393973

In display advertising, click through rate (CTR) prediction is the problem of estimating the probability that an advertisement (ad) is clicked when displayed to a user in a specific context. Due to its easy implementation and promising performance, logistic regression (LR) model has been widely used for CTR prediction, especially in industrial systems. However, it is not easy for LR to capture the nonlinear information, such as the conjunction information, from user features and ad features. In this paper, we propose a novel model, called coupled group lasso (CGL), for CTR prediction in display advertising. CGL can seamlessly integrate the conjunction information from user features and ad features for modeling. Furthermore, CGL can automatically eliminate useless features for both users and ads, which may facilitate fast online prediction. Scalability of CGL is ensured through feature hashing and distributed implementation. Experimental results on real-world data sets show that our CGL model can achieve state-of-the-art performance on web- scale CTR prediction tasks. Copyright © (2014) by the International Machine Learning Society (IMLS) All rights reserved.

关键词： Forecasting

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A Novel Performance Evaluation Method for Visual Tracking Methods

A Novel Performance Evaluation Method for Visual Tracking Me...

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2015年中国智能自动化学术会议

作者： Hui Teng Lianzhi Yu Huaping Liu Fuchun Sun Xiaojuan Liu Department of Computer Science and Technology State Key Laboratory of Intelligent Technology and Systems TNLIST Tsinghua University School of Optical Electrical and Computer Engineering University of Shanghai for Science and Technology

The evaluation for visual tracking is of utmost importance in computer vision. During the last two decades, several evaluation frameworks have been proposed and applied by a large amount of researchers, such as average central error, success rate, or Pascal score. It turns out that it is not easy to compare trackers fairly, precisely, and comprehensively with just only one evaluation index. Given the fact, a novel method for the evaluation of visual tracking algorithms is proposed in this paper, which combines both central error and Pascal score. Using this metric,an experimental validation was conducted finally and may serve as a reference for related research.

关键词： Visual tracking Evaluation Pascal score Central error

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Tracking Salient keypoints for Human Action Recognition

Tracking Salient Keypoints for Human Action Recognition

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IEEE International Conference on systems, Man and Cybernetics

作者： Hanli Wang Yun Yi Key Laboratory of Embedded System and Service Computing Tongji University Shanghai China Department of Mathematics and Computer Science Gannan Normal University Ganzhou China

ISBN: (纸本)9781479986989

It plays an important role to recognize human actions from realistic videos in multimedia event detection and understanding. To this aim, a novel human tracking approach is proposed in this paper. Firstly, salient key points trajectories are generated to track human actions at multiple spatial scales. Then, camera motion elimination is utilized to further improve the robustness of motion trajectories. To depict human motions accurately and efficiently, the Histogram of Oriented Gradient (HOG), Histogram of Optical Flow (HOF) and Motion Boundary Histogram (MBH) are employed with the Fisher vector model being utilized to aggregate these three features. Extensive experimental results on four challenging human action video datasets demonstrate that the proposed approach is able to achieve better recognition performances in a more computationally efficient manner as compared with a number of state-of-the-art approaches.

关键词： Trajectory Videos Tracking Cameras Robustness Feature extraction Optical saturation

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A new logistic map based chaotic biogeography-based optimization approach for cluster analysis

A new logistic map based chaotic biogeography-based optimiza...

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IEEE International Conference on Progress in Informatics and computing (PIC)

作者： Shui-Hua Wang Hui-Min Lu Yu-Jie Li Yang Wang Zhi-Min Chen Yu-Min Wei Wen-Juan Jia Fang-Yuan Liu Yu-Dong Zhang Hunan Provincial Key Laboratory of Network Investigational Technology Hunan Policy Academy Changsha Hunan China School of Computer Science and Technology Nanjing Normal University Nanjing Jiangsu China Department of Electrical Engineering CUNY New York NY USA Department of Mechanical and Control Engineering Kyushu Institute of Technology Fukuoka Prefecture Japan School of Information Engineering Yangzhou University Yangzhou Jiangsu China School of Physics and Electronic Engineering Taizhou University Taizhou Zhejiang China School of Electronic Information Shanghai Dianji University Shanghai China School of Energy and Mechanical Engineering Nanjing Normal University Nanjing Jiangsu China Key Laboratory of Intelligent Computing and Information Processing in Fujian Provincial University Quanzhou Normal University Quanzhou Fujian China

ISBN: (纸本)9781509034857

Cluster analysis is important in scientific and industrial fields. In this study, we proposed a novel chaotic biogeography-based optimization (CBBO) method, and applied it in centroid-based clustering methods. The results over three types of simulation data showed that this proposed CBBO method gave better performance than chaotic particle swarm optimization, genetic algorithm, firefly algorithm, and quantum-behaved particle swarm optimization. In all, our CBBO method is effective in centroid-based clustering.

关键词： Genetic algorithms Optimization Clustering algorithms Particle swarm optimization Algorithm design and analysis Logistics Mathematical model

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Null space based discriminant sparse representation large margin for face recognition

Null space based discriminant sparse representation large ma...

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International Joint Conference on Neural Networks (IJCNN)

作者： Ying Wen Lili Hou Lianghua He Department of Computer Science and Technology East China Normal University Shanghai China Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai China

ISBN: (纸本)9781479919611

In this paper, we propose a novel subspace learning algorithm, termed as null space based discriminant sparse representation large margin (NDSLM). There are two contributions in the paper. First, we propose a new expectation to obtain the neighborhood information for large margin subspace learning, i.e., the within-neighborhood scatter and between-neighborhood scatter are modeled by the sparse reconstruction weights of the samples from the same class and different classes, respectively. Since the neighborhood information formed by sparse representation can capture non-linearities in the data, the proposed method possesses more discriminative information than the traditional large margin learning methods with the expectation using Euclidean distance, etc. Second, the large margin information integrated into the model of Fisher criterion makes the discriminating power of NDSLM further boosted. NDSLM addresses the small sample size problem by solving an eigenvalue problem in null space. Experiments on ORL, Yale, AR, Extended Yale B and CMU PIE five face databases are performed to evaluate the proposed algorithm and the results demonstrate the effectiveness of NDSLM.

关键词： Principal component analysis Silicon Pipelines Glass Databases

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Combining Symbolic Execution and Model Checking for Data Flow Testing 15

Combining Symbolic Execution and Model Checking for Data Flo...

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International Conference on Software Engineering (ICSE)

作者： Ting Su Zhoulai Fu Geguang Pu Jifeng He Zhendong Su Shanghai Key Laboratory of Trustworthy Computing East China Normal University Shanghai China Department of Computer Science University of California Davis USA East China Normal University Shanghai CN

ISBN: (纸本)9781479919345

Data flow testing (DFT) focuses on the flow of data through a program. Despite its higher fault-detection ability over other structural testing techniques, practical DFT remains a significant challenge. This paper tackles this challenge by introducing a hybrid DFT framework: (1) The core of our framework is based on dynamic symbolic execution (DSE), enhanced with a novel guided path search to improve testing performance, and (2) we systematically cast the DFT problem as reach ability checking in software model checking to complement our DSE-based approach, yielding a practical hybrid DFT technique that combines the two approaches' respective strengths. Evaluated on both open source and industrial programs, our DSE-based approach improves DFT performance by 60~80% in terms of testing time compared with state-of-the-art search strategies, while our combined technique further reduces 40% testing time and improves data-flow coverage by 20% by eliminating infeasible test objectives. This combined approach also enables the cross-checking of each component for reliable and robust testing results.

关键词： Search problems Model checking Discrete Fourier transforms Software Engines Safety

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Search for heavy resonances decaying to a Z boson and a photon in pp collisions at s=13 TeV with the ATLAS detector

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Physics Letters, Section B: Nuclear, Elementary Particle and High-Energy Physics 2017年 764卷 11-30页

作者： Aaboud, M. Aad, G. Abbott, B. Abdallah, J. Abdinov, O. Abeloos, B. Aben, R. AbouZeid, O.S. Abraham, N.L. Abramowicz, H. Abreu, H. Abreu, R. Abulaiti, Y. Acharya, B.S. Adachi, S. Adamczyk, L. Adams, D.L. Adelman, J. Adomeit, S. Adye, T. Affolder, A.A. Agatonovic-Jovin, T. Agricola, J. Aguilar-Saavedra, J.A. Ahlen, S.P. Ahmadov, F. Aielli, G. Akerstedt, H. Åkesson, T.P.A. Akimov, A.V. Alberghi, G.L. Albert, J. Albrand, S. Alconada Verzini, M.J. Aleksa, M. Aleksandrov, I.N. Alexa, C. Alexander, G. Alexopoulos, T. Alhroob, M. Ali, B. Aliev, M. Alimonti, G. Alison, J. Alkire, S.P. Allbrooke, B.M.M. Allen, B.W. Allport, P.P. Aloisio, A. Alonso, A. Alonso, F. Alpigiani, C. Alshehri, A.A. Alstaty, M. Alvarez Gonzalez, B. Álvarez Piqueras, D. Alviggi, M.G. Amadio, B.T. Amako, K. Amaral Coutinho, Y. Amelung, C. Amidei, D. Amor Dos Santos, S.P. Amorim, A. Amoroso, S. Amundsen, G. Anastopoulos, C. Ancu, L.S. Andari, N. Andeen, T. Anders, C.F. Anders, G. Anders, J.K. Anderson, K.J. Andreazza, A. Andrei, V. Angelidakis, S. Angelozzi, I. Anger, P. Angerami, A. Anghinolfi, F. Anisenkov, A.V. Anjos, N. Annovi, A. Antel, C. Antonelli, M. Antonov, A. Anulli, F. Aoki, M. Aperio Bella, L. Arabidze, G. Arai, Y. Araque, J.P. Arce, A.T.H. Arduh, F.A. Arguin, J-F. Argyropoulos, S. Arik, M. Armbruster, A.J. Armitage, L.J. Arnaez, O. Arnold, H. Arratia, M. Arslan, O. Artamonov, A. Artoni, G. Artz, S. Asai, S. Asbah, N. Ashkenazi, A. Åsman, B. Asquith, L. Assamagan, K. Astalos, R. Atkinson, M. Atlay, N.B. Augsten, K. Avolio, G. Axen, B. Ayoub, M.K. Azuelos, G. Baak, M.A. Baas, A.E. Baca, M.J. Bachacou, H. Bachas, K. Backes, M. Backhaus, M. Bagiacchi, P. Bagnaia, P. Bai, Y. Baines, J.T. Baker, O.K. Baldin, E.M. Balek, P. Balestri, T. Balli, F. Balunas, W.K. Banas, E. Banerjee, Sw. Bannoura, A.A.E. Barak, L. Barberio, E.L. Barberis, D. Barbero, M. Barillari, T. Barisits, M-S Barklow, T. Barlow, N. Barnes, S.L. Barnett, B.M. Barnett, R.M. Barnovska-Blenessy, Z. Baroncelli, A. Barone, G. Barr, A.J. Barranco Navarro, L. Barreiro, F. Barreiro Gui Department of Physics University of Adelaide Adelaide Australia Physics Department SUNY Albany Albany NY United States Department of Physics University of Alberta Edmonton AB Canada Department of Physics Ankara University Ankara Turkey Istanbul Aydin University Istanbul Turkey Division of Physics TOBB University of Economics and Technology Ankara Turkey LAPP CNRS/IN2P3 Université Savoie Mont Blanc Annecy-le-Vieux France High Energy Physics Division Argonne National Laboratory Argonne IL United States Department of Physics University of Arizona Tucson AZ United States Department of Physics The University of Texas at Arlington Arlington TX United States Physics Department University of Athens Athens Greece Physics Department National Technical University of Athens Zografou Greece Department of Physics The University of Texas at Austin Austin TX United States Institute of Physics Azerbaijan Academy of Sciences Baku Azerbaijan Institut de Física d'Altes Energies (IFAE) The Barcelona Institute of Science and Technology Barcelona Spain Institute of Physics University of Belgrade Belgrade Serbia Department for Physics and Technology University of Bergen Bergen Norway Physics Division Lawrence Berkeley National Laboratory University of California Berkeley CA United States Department of Physics Humboldt University Berlin Germany Albert Einstein Center for Fundamental Physics Laboratory for High Energy Physics University of Bern Bern Switzerland School of Physics and Astronomy University of Birmingham Birmingham United Kingdom Department of Physics Bogazici University Istanbul Turkey Department of Physics Engineering Gaziantep University Gaziantep Turkey Istanbul Bilgi University Faculty of Engineering and Natural Sciences Istanbul Turkey Bahcesehir University Faculty of Engineering and Natural Sciences Istanbul Turkey Centro de Investigaciones Universidad Antonio Narino Bogota Colombia INFN Sezione di Bologna Italy Dipartimento di Fis

This Letter presents a search for new resonances with mass larger than 250 GeV, decaying to a Z boson and a photon. The dataset consists of an integrated luminosity of 3.2 fb−1 of pp collisions collected at s=13 TeV w... 详细信息

This Letter presents a search for new resonances with mass larger than 250 GeV, decaying to a Z boson and a photon. The dataset consists of an integrated luminosity of 3.2 fb⁻¹ of pp collisions collected at s=13 TeV with the ATLAS detector at the Large Hadron Collider. The Z bosons are identified through their decays either to charged, light, lepton pairs (e⁺e⁻, μ⁺μ⁻) or to hadrons. The data are found to be consistent with the expected background in the whole mass range investigated and upper limits are set on the production cross section times decay branching ratio to Zγ of a narrow scalar boson with mass between 250 GeV and 2.75 TeV. © 2016 The Author(s)

关键词： Z bosons CROSS sections (Nuclear physics) PHOTON-photon interactions LARGE Hadron Collider (France & Switzerland) DILEPTON production NUCLEAR counters

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On deploying relays for connected indoor sensor networks

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Journal of Communications and Networks 2014年第3期16卷 335-343页

作者： Zhu, Yanmin Xue, Cuiyao Cai, Haibin Yu, Jiadi Ni, Lei Li, Minglu Li, Bo Shanghai Key Lab. of Scalable Computing and Systems Department of Computer Science and Engineering Shanghai Jiao Tong University China Department of Computer Science and Engineering Shanghai Jiao Tong University China Software Engineering Institute East China Normal University China Shanghai Jiao Tong University Hong Kong University of Science and Technology Hong Kong

This paper considers the crucial problem of deploying wireless relays for achieving a connected wireless sensor network in indoor environments, an important aspect related to the management of the sensor network. Several algorithms have been proposed for ensuring full sensing coverage and network connectivity. These algorithms are not applicable to indoor environments because of the complexity of indoor environments, in which a radio signal can be dramatically degraded by obstacles such as walls. We first prove theoretically that the indoor relay placement problem is NP-hard. We then predict the radio coverage of a given relay deployment in indoor environments. We consider two practical scenarios;wire-connected relays and radio-connected relays. For the network with wire-connected relays, we propose an efficient greedy algorithm to compute the deployment locations of relays for achieving the required coverage percentage. This algorithm is proved to provide a Hn factor approximation to the theoretical optimum, where Hn = 1 +1/2+⋯+1/n= ln(n) +1, and n is the number of all grid points. In the network with radio-connected relays, relays have to be connected in an ad hoc mode. We then propose an algorithm based on the previous algorithm for ensuring the connectivity of relays. Experimental results demonstrate that the proposed algorithms achieve better performance than baseline algorithms. © 2014 KICS.

关键词： Approximation algorithms

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